Plethysmography Phenotype QTL in Mice Before and After Allergen Sensitization and Challenge

Effects of coffee intake on airway hypersensitivity and immunomodulation: an in vivo murine study

BACKGROUND/OBJECTIVES

Coffee is a complex chemical mixture, with caffeine being the most well-known bioactive substance. The immunomodulatory and anti-inflammatory properties of coffee and caffeine impact health in various aspects, including the respiratory system. The objective is to investigate the effects of coffee and caffeine on airway hyperresponsiveness and allergic reactions, as well as to analyze and compare associated cytokine profiles.

MATERIALS/METHODS

BALB/c mice were intraperitoneally sensitized with ovalbumin (OVA) and given OVA inhalation to induce airway hypersensitivity. Two weeks after sensitization, they were intragastrically gavaged with coffee or caffeine, both containing 0.3125 mg caffeine, daily for 4 weeks. Control mice were fed with double-distilled water. Serum OVA-specific antibody levels were measured beforehand and 5 weeks after the first gavage. Airway hyperresponsiveness was detected by whole body plethysmography after gavage. Cytokine levels of bronchoalveolar lavage and cultured splenocytes were analyzed.

RESULTS

Coffee effectively suppressed T helper 2-mediated specific antibody response. Airway responsiveness was reduced in mice treated with either coffee or caffeine. Compared to the control, coffee significantly reduced OVA-specific immunoglobulin (Ig) G, IgG1 and IgE antibody responses (P < 0.05). Caffeine also attenuated specific IgG and IgG1 levels, though IgE level was unaffected. Coffee significantly reduced interleukin (IL)-4 and increased IL-10 concentration in spleen cells and bronchoalveolar lavage fluid (P < 0.05).

CONCLUSIONS

Coffee effectively attenuated airway hyperresponsiveness and systemic allergic responses induced by OVA food allergen in mice. As a complex composition of bioactive substances, coffee displayed enhanced immunomodulatory and anti-inflammatory effects than caffeine.

A Leak-Free Head-Out Plethysmography System to Accurately Assess Lung Function in Mice

Mice are a valuable model for elegant studies of complex, systems-dependent diseases, including pulmonary diseases. Current tools to assess lung function in mice are either terminal or lack accuracy. We set out to develop a low-cost, accurate, head-out variable-pressure plethysmography system to allow for repeated, non-terminal measurements of lung function in mice. Current head-out plethysmography systems are limited by air leaks that prevent accurate measures of volume and flow. We designed an inflatable cuff that encompasses the mouse's neck preventing air leak. We wrote corresponding software to collect and analyze the data, remove movement artifacts, and automatically calibrate each dataset. This software calculates inspiratory/expiratory volume, inspiratory/expiratory time, breaths per minute, mid-expiratory flow, and end-inspiratory pause. To validate the use, we established that our plethysmography system accurately measured tidal breathing, the bronchoconstrictive response to methacholine, sex and age associated changes in breathing, and breathing changes associated with house dust mite sensitization. Our estimates of volume, flow, and timing of breaths are in line with published estimates, we observed dose-dependent decreases in volume and flow in response to methacholine (P < 0.05), increased lung volume and decreased breathing rate with aging (P < 0.05), and that house dust mite sensitization decreased volume and flow (P <0.05) while exacerbating the methacholine induced increases in inspiratory and expiratory time (P < 0.05). We describe an accurate, sensitive, low-cost, head-out plethysmography system that allows for longitudinal studies of pulmonary disease in mice.

A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes

The collaborative cross (CC) is a large panel of mouse-inbred lines derived from eight founder strains (NOD/ShiLtJ, NZO/HILtJ, A/J, C57BL/6J, 129S1/SvImJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Here, we performed a comprehensive and comparative phenotyping screening to identify phenotypic differences and similarities between the eight founder strains. In total, more than 300 parameters including allergy, behavior, cardiovascular, clinical blood chemistry, dysmorphology, bone and cartilage, energy metabolism, eye and vision, immunology, lung function, neurology, nociception, and pathology were analyzed; in most traits from sixteen females and sixteen males. We identified over 270 parameters that were significantly different between strains. This study highlights the value of the founder and CC strains for phenotype-genotype associations of many genetic traits that are highly relevant to human diseases. All data described here are publicly available from the mouse phenome database for analyses and downloads.

Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation

Gene transcription profiles across tissues are largely defined by the activity of regulatory elements, most of which correspond to regions of accessible chromatin. Regulatory element activity is in turn modulated by genetic variation, resulting in variable transcription rates across individuals. The interplay of these factors, however, is poorly understood. Here we characterize expression and chromatin state dynamics across three tissues-liver, lung, and kidney-in 47 strains of the Collaborative Cross (CC) mouse population, examining the regulation of these dynamics by expression quantitative trait loci (eQTL) and chromatin QTL (cQTL). QTL whose allelic effects were consistent across tissues were detected for 1,101 genes and 133 chromatin regions. Also detected were eQTL and cQTL whose allelic effects differed across tissues, including local-eQTL for Pik3c2g detected in all three tissues but with distinct allelic effects. Leveraging overlapping measurements of gene expression and chromatin accessibility on the same mice from multiple tissues, we used mediation analysis to identify chromatin and gene expression intermediates of eQTL effects. Based on QTL and mediation analyses over multiple tissues, we propose a causal model for the distal genetic regulation of Akr1e1, a gene involved in glycogen metabolism, through the zinc finger transcription factor Zfp985 and chromatin intermediates. This analysis demonstrates the complexity of transcriptional and chromatin dynamics and their regulation over multiple tissues, as well as the value of the CC and related genetic resource populations for identifying specific regulatory mechanisms within cells and tissues.

A GWAS approach identifies Dapp1 as a determinant of air pollution-induced airway hyperreactivity

Asthma is a chronic inflammatory disease of the airways with contributions from genes, environmental exposures, and their interactions. While genome-wide association studies (GWAS) in humans have identified ~200 susceptibility loci, the genetic factors that modulate risk of asthma through gene-environment (GxE) interactions remain poorly understood. Using the Hybrid Mouse Diversity Panel (HMDP), we sought to identify the genetic determinants of airway hyperreactivity (AHR) in response to diesel exhaust particles (DEP), a model traffic-related air pollutant. As measured by invasive plethysmography, AHR under control and DEP-exposed conditions varied 3-4-fold in over 100 inbred strains from the HMDP. A GWAS with linear mixed models mapped two loci significantly associated with lung resistance under control exposure to chromosomes 2 (p = 3.0x10^-6) and 19 (p = 5.6x10^-7). The chromosome 19 locus harbors Il33 and is syntenic to asthma association signals observed at the IL33 locus in humans. A GxE GWAS for post-DEP exposure lung resistance identified a significantly associated locus on chromosome 3 (p = 2.5x10^-6). Among the genes at this locus is Dapp1, an adaptor molecule expressed in immune-related and mucosal tissues, including the lung. Dapp1-deficient mice exhibited significantly lower AHR than control mice but only after DEP exposure, thus functionally validating Dapp1 as one of the genes underlying the GxE association at this locus. In summary, our results indicate that some of the genetic determinants for asthma-related phenotypes may be shared between mice and humans, as well as the existence of GxE interactions in mice that modulate lung function in response to air pollution exposures relevant to humans.

The genetic factors that modulate risk of asthma through gene-environment (GxE) interactions are poorly understood, due in large part to the inherent difficulties in carrying out such studies in humans. To address these challenges, we used the Hybrid Mouse Diversity Panel to elucidate the genetic architecture of asthma-related phenotypes in mice and identify loci that are associated with airway hyperreactivity (AHR) under control exposure conditions and in response to diesel exhaust particles (DEP), as a model traffic-related air pollutant. In the absence of exposure, we identified two loci on chromosomes 2 and 19 for AHR. The locus on chromosome 19 harbors Il33 and is syntenic to association signals observed for asthma at the IL33 locus in humans. In response to DEP exposure, we mapped AHR to a region on chromosome 3 and used a genetically modified mouse model to functionally demonstrate that Dapp1 is one of the genes underlying the GxE association at this locus. Collectively, our results support the concept that some of the genetic determinants for asthma-related phenotypes may be shared between mice and humans as well as the existence of GxE interactions in mice that modulate lung function in response to air pollution exposures relevant to humans.

Determinants of QTL Mapping Power in the Realized Collaborative Cross

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

Incorporating population-level genetic variability within laboratory models in toxicology: From the individual to the population

Humans respond to chemical exposures differently due to many factors, such as previous and concurrent stressors, age, sex, and genetic background. The vast majority of laboratory-based toxicology studies, however, have not considered the impact of population-level variability within dose-response relationships. The lack of data dealing with the influence of genetic diversity on the response to chemical exposure provides a difficult challenge for risk assessment as individuals within the population will display a wide-range of responses following toxicant challenge. Notably, the genetic background of individuals plays a major role in the variability seen in a population-level response to a drug or chemical and, thus, there is growing interest in including genetic diversity into laboratory-models. Here we outline several laboratory-based models that can be used to assay the influence of genetic variability on an individual's response to chemicals: 1) genetically-diverse cell lines, 2) human primary cells, 3) and genetically-diverse mouse panels. We also provide a succinct review for several seminal studies to highlight the capability, feasibility, and power of each of these models. This article is intended to highlight the need to include population-level genetic diversity into toxicological study designs via laboratory-based models with the goal to provide and supplement evidence in assessing the risk posed by chemicals to the human population. As such, incorporation of genetic variability will positively impact human-based risk assessment and provide empirical data to aid and influence decision-making processes in relation to chemical exposures.

Identification of trans Protein QTL for Secreted Airway Mucins in Mice and a Causal Role for Bpifb1

Mucus hyper-secretion is a hallmark feature of asthma and other muco-obstructive airway diseases. The mucin proteins MUC5AC and MUC5B are the major glycoprotein components of mucus and have critical roles in airway defense. Despite the biomedical importance of these two proteins, the loci that regulate them in the context of natural genetic variation have not been studied. To identify genes that underlie variation in airway mucin levels, we performed genetic analyses in founder strains and incipient lines of the Collaborative Cross (CC) in a house dust mite mouse model of asthma. CC founder strains exhibited significant differences in MUC5AC and MUC5B, providing evidence of heritability. Analysis of gene and protein expression of Muc5ac and Muc5b in incipient CC lines (n = 154) suggested that post-transcriptional events were important regulators of mucin protein content in the airways. Quantitative trait locus (QTL) mapping identified distinct, trans protein QTL for MUC5AC (chromosome 13) and MUC5B (chromosome 2). These two QTL explained 18 and 20% of phenotypic variance, respectively. Examination of the MUC5B QTL allele effects and subsequent phylogenetic analysis allowed us to narrow the MUC5B QTL and identify Bpifb1 as a candidate gene. Bpifb1 mRNA and protein expression were upregulated in parallel to MUC5B after allergen challenge, and Bpifb1 knockout mice exhibited higher MUC5B expression. Thus, BPIFB1 is a novel regulator of MUC5B.